Matching Resources in Social Environment

dc.contributor.authorBenna, Amel
dc.contributor.authorMellah, Hakima
dc.contributor.authorChoui, Islam
dc.contributor.authorOualid, Ali
dc.description.abstractUser comments on the web are becoming more and more important. We focus, in this paper, on the use of user-defined tags for annotating resources to identify links between them. These links are based on a social context of the resource, obtained by applying k-means classification method and a hierarchi- cal classification of tags within a cluster. The resources are re-assigned to this classification to facilitate the search process. The ranking of results is performed according to their degree of relevance, by evaluating a similarity score between the tagged contents, in hierarchical clusters of tags, and the user request. The re- sults of the evaluation, on the social bookmarking, demonstrate significant improvements over traditional approaches.fr_FR
dc.relation.ispartofInternational Workshop on Web Intelligence in conjunction with International Conference on Entreprise Information systems (ICEIS)fr_FR
dc.relation.placeWroclaw, Polandfr_FR
dc.structureIntégration des Systèmes d'Informationfr_FR
dc.subjectCollaborative taggingfr_FR
dc.subjectSocial information retrievalfr_FR
dc.subjectMatching resourcesfr_FR
dc.titleMatching Resources in Social Environmentfr_FR
dc.typeConference paper